https://julialang.org/downloads/ 的提示来下载并安装 Julia。 启动一个交互式会话（也叫 REPL）是学习和尝试 Julia 最简单的方法。双击 Julia 的可执行文件或是从 命令行运行 julia 就可以启动： $ julia _ _ _ _(_)_ | Documentation: https://docs.julialang.org (_) | (_) (_) | 如果想非交互式地执行文件中的代码，可以把文件名作为 julia 命令的第一个参数： $ julia script.jl arg1 arg2... 如这个例子所示，julia 后跟着的命令行参数会被作为程序 script.jl 的命令行参数。这些参数使用 全局常量 ARGS 来传递，脚本自身的名字会以全局变量 PROGRAM_FILE 传入。注意当脚本以命令行里的 -e 选项输入时，ARGS 也会被设定（详见此页末尾列表）但是 end' > script.jl $ julia script.jl foo bar script.jl foo bar 可以使用 -- 分隔符来将传给脚本文件的参数和 Julia 本身的命令行参数区分开： $ julia --color=yes -O -- foo.jl arg1 arg2.. 有关编写 Julia 脚本的更多信息，请参阅 脚本。 使用选项 -p 或者 --machine-file

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 28.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 27.1 Propagation of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 29.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the